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Record W2087530045 · doi:10.4141/s06-018

Quantifying carbon sequestration in a minimum tillage crop rotation study in semiarid southwestern Saskatchewan

2007· article· en· W2087530045 on OpenAlexaffvenueabout
C. A. Campbell, A.J. VandenBygaart, R.P. Zentner, B.G. McConkey, Ward Smith, R. Lemke, Brian Grant, P. G. Jefferson

Bibliographic record

VenueCanadian Journal of Soil Science · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsGenome PrairieAgriculture and Agri-Food Canada
Fundersnot available
KeywordsCrop rotationEnvironmental scienceCarbon sequestrationTillageChernozemSoil carbonCrop residueSoil waterCropping systemAgronomyGrowing seasonCropSoil scienceAgricultureGeographyCarbon dioxideEcology

Abstract

fetched live from OpenAlex

Scientists and the agricultural community require methods of quantifying C sequestration in soils. This is important in assessing the impact of crop management practices on emission of greenhouse gases and for “C trading”. Using simulation models may be a more effective method of quantification as compared with in situ measurements. A 17-yr crop rotation experiment being conducted on a medium-textured Orthic Brown Chernozem at Swift Current, Saskatchewan, in which soil organic C (SOC) was being monitored periodically, was used to assess the effect on C sequestration of cropping frequency, wheat class, legume green manure (LGM), flexible cropping based on available water, and regrassing of crop land. Prior to the study, the experimental site had been cropped to fallow-wheat (F-W) for the previous 60 yr. Crop management in this experiment involved minimum tillage, snow trapping, and N + P fertilization based on soil tests. Three models [Century, the Introductory C Balance model (ICBM), and the Campbell model] were tested for their effectiveness in simulating SOC trends. Because growing season precipitation was average to above average, yields, and thus C inputs from residue, were also above average, and consequently SOC increased in most systems for the first 10 yr before reaching a new steady state. SOC gains (kg ha -1 yr -1 ) in the 0- to 15-cm depth in 17 yr were directly proportional to cropping frequency (F-W-W = 135, F-W-W-W = 332, and Cont W = 441); LGM-W-W gained SOC at a much higher rate than F-W-W (329 vs. 135 kg ha -1 yr -1 ); Canada Western Red Spring (CWRS) wheat (Triticum aestivum L.), although it yielded 26% less than Canada Prairie Spring (CPS) wheat, gained SOC at a higher rate than CPS wheat (135 vs. 0 kg ha -1 yr -1 ). Further, 2 yr of conventionally-tilled fallow in 17 yr (flexible system) markedly suppressed SOC gain by 46% compared with Cont W (441 vs. 236 kg ha -1 yr -1 ). There was a 282 kg ha -1 yr -1 gain in SOC under crested wheatgrass (Agropyron cristatum L.) (CWG) but most of this gain occurred in the last 7 yr. Though having their inherent weaknesses, the ICBM and Campbell models performed equally well in simulating SOC trends (r 2 = 0.55**), but Century was less effective (r 2 = 0.21*), in part because of its limited ability to simulate yields. Because C input, and thus yield, is one of the main factors influencing SOC gains, and since measured yields are used in the ICBM and Campbell models, while simulated yields are used by Century, the ICBM and Campbell models have an advantage over the Century model in this comparison. Efficiencies of conversion of input C to SOC increased with cropping frequency, and were higher for LGM-W-W than for F-W-W, and for systems with CWRS wheat rather than CPS wheat. Efficiency of conversion was 8% for F-W-W, 15% for LGM-W-W and 21% for Cont W. Key words: ICBM model, Century model, Campbell model, C sequestration, legume green manure, regrassing

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.797
Threshold uncertainty score0.815

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.259
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations51
Published2007
Admission routes3
Has abstractyes

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